Re: st:Survival analysis - dealing with Right truncated data

Because you utilize no information about those who did not fail, you can
say _nothing_ about the impact of covariates on survival.
Example: compare 2 groups
1. Your data
Failures
Group 1: 1 2
Group 2: 9 10
What can be said: of those who failed, failures in group 2
were later. But this does _not_ mean that survival was
better in group 2.
2. Complete Data
Group 1: Failures 1 2 Not Failed 11 12 13
Group 2: Failures 9 10 Not failed 0
Percent who failed through T = 10
Group 1 20%
Group 2 100%
Steve
sjsamuels@gmail.com
On Aug 17, 2012, at 10:15 AM, Phakathi, T.R. wrote:
The dataset ONLY includes observations that have failed (Right truncation). For those that have failed (in this case all who lost employment), there are details on the risk onset and failure date including individual and firm characteristics.
I would like to estimate the impact of the covariates on Survival. Are the commands distinct from “normal” survival data? If so what are the available commands (Non/Semi &parametric)?
May I tap into the wealth of your experiences
Thank you
Themba Phakathi
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